How AI-Powered Prosthetics Leverage Neural Learning for Precision

For most of us, moving our hands feels natural. We don’t think about it—we just reach, hold, or lift. But for someone using a prosthetic, every movement is a careful effort. The hand responds, but not always the way they want. It can feel slow, clumsy, or disconnected. Now imagine a prosthetic that doesn’t just […]
Machine Learning Meets the Brain: Adaptive Algorithms for Prosthetic Control

Imagine trying to use a prosthetic hand that doesn’t quite understand you. You think about closing your fist, but the response is slow, clumsy, or just not what you intended. This is the challenge many prosthetic users face today. Now imagine a prosthetic that doesn’t just follow commands, but actually learns from you. A hand […]
Closed-Loop Bionic Control: Why Neuroplasticity Needs Feedback

When someone loses a limb and gets a prosthetic, most people think the goal is to move again. And while that’s true, it’s only part of the story. What really matters—what truly changes lives—is control. Not just the ability to move a bionic hand, but to feel in charge of it. To trust it. To […]
EMG vs EEG vs IMU: Which Neural Inputs Work Best for Adaptive Bionics?

Modern bionic limbs are no longer just machines. They are smart, intuitive, and deeply connected to the human body. But to make them move in a natural and responsive way, they need to understand what the body is trying to say. This starts with reading the right signals. Those signals can come from the brain, […]
How the Brain Learns a New Hand: Insights into Bionic Neuroplasticity

When someone loses a hand and receives a bionic one, the journey doesn’t end with surgery or fitting. It begins with something deeper—learning. The brain must now figure out how to control this new hand. How to move it. How to trust it. How to make it feel like part of the body again. This […]